What's the difference between architectures and backbones?
The vocabulary is definitely non-standard and a bit confusing, but Feature Pyramid Networks is used as a feature extractor, and its output is then fed into EfficientNet-B2 to be used to classify the image. One neural network model is concatenated at the end of the other.
So it seems like &quot;architecture&quot; is the front half of the neural network model which takes as input the satellite image and extracts image featuers, and then is directly connected to the back half of the model (hence &quot;backbone&quot;), which takes the features extracted from the &quot;architecture&quot; and makes a classification.
This terminology is definitely non-standard here, at least in the AI community, and if you ask anyone here I think it will be uncommon for them to naturally think about the words &quot;architecture&quot; vs &quot;backbone&quot; in this way unless they specialize in a similar field to the authors.